NIQuery: Neuroimaging Informatics Query Framework for Data Sharing, Discovery, and Analysis
B. Nolan Nichols (Integrated Brain Imaging Center, University of Washington, Seattle, WA), Robert F. Dougherty (Center for Cognitive and Neurobiological Imaging, Stanford University, Stanford, CA), Landon T. Detwiler (Integrated Brain Imaging Center, University of Washington, Seattle, WA), Gunnar Schaefer (Center for Cognitive and Neurobiological Imaging, Stanford University, Stanford, CA), Randall J. Frank (Integrated Brain Imaging Center, University of Washington, Seattle, WA), James F. Brinkley (Integrated Brain Imaging Center, University of Washington, Seattle, WA), Brian A. Wandell (Center for Cognitive and Neurobiological Imaging, Stanford University, Stanford, CA), Thomas J. Grabowski (Integrated Brain Imaging Center, University of Washington, Seattle, WA)
The protocol supporting this functionality consists of: 1) a persistent Session object that wraps databases (e.g. XNAT[1], NIMS[2], Allen Institute[3]), exposes the NIQuery application programming interface, and serves objects and requests; 2) a Query object that provides a mechanism to interrogate databases with user defined and/or predefined web-accessible queries; 3) a Data object conforming to a supported 'image' data model (e.g., DICOM, NIfTI, etc.) that provides a mechanism to return pixel data to an application; and 4) a Workflow object through which a server provides a computational service on a Data object. A registry service (www.niquery.org) provides an index of available NIQuery servers, as well as the query, data, and workflow objects available on each server.
NIQuery enables client applications to discover shared neuroimaging data using metadata-level distributed queries and then execute image processing workflows on discovered data at their source, on a cached copy in the cloud, or locally. A sample implementation of this framework involves exporting a snapshot of XNAT and NIMS databases into XCEDE XML files, indexing the snapshots with the NIQuery registry service, and remotely calculating quality control metrics on resting-state fMRI data. These informatics tools will support agile exploration and reuse of open access neuroimaging data.
References
1. Marcus DS, Olsen TR, Ramaratnam M, Buckner RL. The Extensible Neuroimaging Archive Toolkit: an informatics platform for managing, exploring, and sharing neuroimaging data. Neuroinformatics.
2. Neurobiological Image Management System. http://github.com/cni/nims
3. Zeng H, et. al. 2012. Large-Scale Cellular-Resolution Gene Profiling in Human Neocortex Reveals Species-Specific Molecular Signatures. Cell.